A comparison of various approaches to the Exponential Random Graph Model: A reanalysis of 102 student networks in school classes

TitleA comparison of various approaches to the Exponential Random Graph Model: A reanalysis of 102 student networks in school classes
Publication TypeJournal Article
Year of Publication2007
AuthorsLubbers, MJ
Secondary AuthorsSnijders, TAB
JournalSocial Networks
Volume4
Start Page489-507
Issue29
KeywordsSocial networks; ERGM; Dependence structure
Abstract

This paper describes an empirical comparison of four specifications of the exponential family of random graph models (ERGM), distinguished by model specification (dyadic independence, Markov, partial conditional dependence) and, for the Markov model, by estimation method (Maximum Pseudolikelihood, Maximum Likelihood). This was done by reanalyzing 102 student networks in 57 junior high school classes. At the level of all classes combined, earlier substantive conclusions were supported by all specifications.However, the different specifications led to different conclusions for individual classes. PL produced unreliable estimates (whenMLis regarded as the standard) and had more convergence problems than ML. Furthermore, the estimates of covariate effects were affected considerably by controlling for network structure, although the precise specification of the structural part (Markov or partial conditional dependence) mattered less.
© 2007 Elsevier B.V. All rights reserved.

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